Method and device for improving prediction and detection of adverse events in elderly or disabled people

ABSTRACT

Embodiments relates to a method, apparatus and system comprising a resting device for resting a patient, the resting device comprising a substrate having a contact surface for contacting the patient, one or more sacs comprising a material and associated with the contact surface of the substrate, one or more sensors that are incorporated in the one or more sacs, and a patient recognition algorithm to detect changes in a user profile; wherein the system is configured to at least (a) combine information and construct the user profile, wherein the information comprises a first data from a pressure ulcer risk scale and a second data obtained via the resting device over time, and (b) automatically perform an assessment of a risk of pressure ulcer in the patient.

RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.16/362,755, filed on Mar. 25, 2019 which is a continuation of U.S.patent application Ser. No. 15/595,599, filed on May 15, 2017 (now U.S.Pat. No. 10,238,342, issued on Mar. 26, 2019), which claims the benefitof priority of U.S. Provisional Application No. 62/336,084, filed May13, 2016, and is a continuation-in-part of U.S. patent application Ser.No. 15/583,989, filed on May 1, 2017 (now U.S. Pat. No. 10,123,734,issued Nov. 13, 2018), which is a continuation of U.S. patentapplication Ser. No. 14/433,597, filed Apr. 3, 2015 (now U.S. Pat. No.9,636,045, issued May 2, 2017), which is the U.S. national phase entryof International Patent Application No. PCT/IB2013/002919, filed on Oct.7, 2013, which claims the benefit of foreign priority of Danish PatentApplication No. PA 2012 70605, filed on Oct. 5, 2012, and all of theabove applications are herein incorporated in their entirety byreference.

TECHNICAL FIELD

This disclosure relates generally to monitoring and prevention ofhealth-related conditions of a person, and in particular, to a methodand apparatus for monitoring and preventing pressure ulcers and for riskstratification, monitoring, detection and prediction of adverse eventsin bedridden people.

BACKGROUND ART

Elderly, bedridden patients, wheelchair bound patients, people withlimited mobility or reduced sensation of touch, e.g. those sufferingfrom diabetic neuropathy, have high risk of developing adverse events.Pressure ulcers, also called bed sores, are a major health issue.Bedridden patients, wheelchair bound patients, people with limitedmobility or reduced sensation of touch, e.g. those suffering fromdiabetic peripheral neuropathy, have high risk of developing pressureulcers. Pressure ulcers (PUs) can develop quickly and are painful forthe patient. They are generally resistant to known medical therapy and,are often very difficult to heal. PUs can cause reduced anatomical orfunctional integrity in patients and can, occasionally lead to lifethreatening complications. Care for patients suffering from PUs is oftentime consuming, personnel intensive and expensive. Once developed, PUsincreased hospital stay, imposing enormous burden on the healthcaresystem and diverting precious personnel resources that may be allocatedfor other patients. Pressure ulcers, also called bed sores, are a majorhealth issue. Furthermore, day-to-day increased in body temperature orweight loss will increase the risk of PUs and may by a symptom ofanother advance event like dehydration.

Either static or long-term dynamic or punctual load, which allowspressure marks on an insensitive or passive area on the body, can leadto pressure ulcers if not taken care of in time. Such occurrences ofpressure can occlude blood supply to parts of the body leading to tissueischemia. If such pressure is not relieved over a long period of timetissue ischemia can lead to permanent cell damage causing pressureulcers. The person with normal sensation and mobility would beimmediately alerted while the person without sensation or reducedmobility—allows repeated high pressure and/or static load on the samesmall place on the body. This can create sores or precursors thereof.

For example, patients suffering from diabetic neuropathy have reducedsensation in their extremities and may not sense a wound or skin damageto their hands and/or feet. In such patients, a wound or skin damage onthe foot can occur without detection, and the condition can lead tocomplications such as severe infection, slow healing wounds and risk ofamputation. Therefore it becomes important for staff at the hospital ornursing home to constantly monitor vulnerable areas of the body andespecially observe pressure related alteration of the skin that may beprecursors of pressure ulcer.

So far, the most effective care for an at-risk patient is to relieve thepressure which, in hospitals, is commonly done by periodicallyrepositioning bed-bound patients. Because every patient has levels ofrisk of occurrence of PUs depending on factors such as age, sex, diseaseconditions, blood pressure, nutrition, etc., some patients may need morefrequent repositioning than others. Determining the schedule forrepositioning is difficult may yet be unable to prevent occurrence ofPUs.

Existing pressure relieving massage mattresses with inflatable chambers,where the different chambers are inflated and deflated in differentintervals. The desired effect of these massage mattresses are relocationof the weight loads of the patient prolonging the time span the patientis able to be in the same position without developing a PU. Thesemassage mattresses do not reposition the patient which is vital to avoidPU's and they increase the shear stress on the patient skin whileinflating and deflating, which may also lead to develop PU's.

Devices for monitoring patients to prevent and/or detect PUs generallyinclude an array of pressure sensors placed in close proximity to partsof a patient's body that are at a higher risk of forming PUs. Thepressure sensors record pressure on the at-risk parts and provide thedata to a caregiver so that the caregiver may relive the excess pressurefrom particular parts by suitably repositioning the patient. However, ingenerally, such devices are expensive and do not, by themselves, absorbor relieve pressure. For example, it would be rather expensive to changea sock having an array of pressure sensors on a daily basis.Furthermore, there may be problems with machine washing and/orautoclaving, as the connection (e.g., a cable) from the sensor to theelectronics may not be adequately protected. Moreover, such devicestechnologies fail to utilize pressure relieving and shock absorbingareas of the patient's body that could otherwise be used. Furthermore,the dimensions of sensor array devices and spatial constraints forplacing these arrays in proximity to a certain body part limit theavailable locations for placement of such devices. For example, while itmay be suitable to use such devices on a mattress or a sheet, it may notwork in a shoe or a sock because of the limited space available forplacing the sensor without chaffing the user's foot.

Today the development of acquired PU is still of great concern inhospitalized health care. In the United States, PU are observed in morethan 500,000 annual inpatient hospital stays. PU is a painful,incapacitating and potentially fatal complication to routine medical andnursing care. Treatment of pressure ulcers is very costly, and thedevelopment of pressure ulcers can be prevented by integrating dedicateduse of evidence-based best nursing practice. In the United Kingdom aloneup to an estimated English Pound.2.1 billion are used annually to treatpressure ulcers—this corresponds to 4% of the National Health Servicebudget. In addition to the increased cost, the length of the hospitalstay will be prolonged and patient recovery will be delayed as well. PUnormally results from long periods with continuous pressure and shearinduced to the skin and underlying soft and muscle tissue, and bonyprominences. High risk patients are elderly people, stroke patients,people with diabetes, individuals with dementia, persons who usewheelchairs or are bedbound, and any patient with reduced mobility.

Often the prevention and treatment of PU are performed unsystematic andbased on clinical experience of the individual health care provider.Predictive models have the potential to improve the management andprevention of PU. We have previously shown in a different medical domainhow predictive models that fusing of information from differentmodalities could potentially help preventing serious disease. Severalrisk scores assessing the patient's risk of developing PU have beenproposed and used in medical care such as the Braden, Waterlow andNorton scale. However, the predictive values of these risk-scales haveshown low to modest accuracy and are not used in combination with sensormattress.

SUMMARY

The embodiments herein relate to a system comprising a resting devicefor resting a patient, wherein the system is configured to collectinformation from the patient via the resting device over time andconstruct a user profile of the patient who is laying on the restingdevice, furthermore, the resting device comprises a patient applicationrecognition algorithm to detect changes in the user profile of thepatient and thereby predict in advance any potential adverse healtheffect on the patient. The resting device could comprise a wirelesssensor with a built-in pressure sensor. The system is configured toprovide an automatic feedback from the patient application recognitionalgorithm to the patient using light, words, text message or alarm. Thesystem is further configured to provide the automatic feed to aprofessional health care giver. The resting device comprises a mattressor chair.

In further embodiments herein, the system is configured to undertakerisk stratification, predication and detection. The resting devicecomprises a contact surface for contacting the patient and has one ormore voxels or areas that are able to transmit pressure using amaterial. The material that transmits pressure is also shock-absorbingand pressure relieving. The resting device comprises a pressuredetection device over voxels or areas, wherein the pressure detectiondevice comprises the built-in pressure sensor that comprises a forceresistant film or a piezo-electric sensitive material. The built-inpressure sensor is combined with or part of an identification chip or aradio frequency identification chip that is configured to sendinformation to a receiver. If one sends radio signal to the chip, thechip can detect the information, get activated, and send the informationthat the chip has measured back to the receiver.

In an embodiment, a device includes five components: (1)pressure-relieving embodiment e.g. a mattress (2) with one or moresensors (3) a microchip containing a pattern recognition algorithm/modela (4) mobile application for care monitoring and (5) a patient feedbacksystem using one or more of audio, visual, audiovisual or haptic signalthat prompt the patient to perform a preventing action e.g.self-turning. The combination of these five components will enable thepresent invention to predict adverse events in bedridden people and indue time warn the professional personal or the patient. Thus, preventinga serious incident.

In an embodiment, a device includes a substrate having a contact surfacefor contacting a user, one or more sacs associated with the contactsurface of the substrate, and one or more sensors in communication withthe one or more sacs, the one or more sensors adapted to measure changesin pressure in the one or more sacs. The sacs contain a materialconfigured to transmit pressure. The material is further configured tobe shock-absorbing and pressure-relieving such that the material isdisplaceable by an action of the user contacting the contact surfacecausing the pressure in the material to be redistributed. The one ormore sensors adapted to measure changes in pressure in the one or moresacs.

In an embodiment, a device includes a substrate having a contact surfacefor contacting a user, one or more sacs associated with the contactsurface of the substrate, and one or more sensors in communication withthe one or more sacs, the one or more sensors adapted to measure changesin pressure in the one or more sacs. The sacs contain a materialconfigured to transmit pressure. The material is further configured tobe shock-absorbing and pressure-relieving such that the material isdisplaceable by an action of the user contacting the contact surfacecausing the pressure in the material to be redistributed. Changes inpressure in the one or more sacs are measured using one or more sensorsin communication with the one or more sacs.

In an embodiment, a system includes (i) a device having a substratehaving a contact surface for contacting a user and one or more materialfilled sacs associated with the contact surface of the substrate, (ii) acontroller configured to transmit and/or receive radio frequency signalsto and from the one or more sensors corresponding to the measuredchanges in pressure, and (iii) a user feedback device in communicationwith the controller. a substrate having a contact surface for contactinga user, one or more sacs associated with the contact surface of thesubstrate, and one or more sensors in communication with the one or moresacs, the one or more sensors adapted to measure changes in pressure inthe one or more sacs. The sacs contain a material configured to transmitpressure. The material is further configured to be shock-absorbing andpressure-relieving such that the material is displaceable by an actionof the user contacting the contact surface causing the pressure in thematerial to be redistributed. The user feedback device configured toprovide an indication to a user based on the measured changes inpressure. Changes in pressure in the one or more material filled sacsare measured using one or more sensors in communication with the one ormore material filled sacs.

In an embodiment, a method includes measuring pressure exerted by aportion of a subject's body on one or more sacs associated with asubstrate having a contact surface for contacting with the portion ofthe subject's body to provide pressure information and transmitting thepressure information to a receiving station. The pressure informationindicates, using one or more of audio, visual, audiovisual or hapticsignal.

A pressure-relieving embodiment, example giving a mattress, a seat, apillow or a shoe sole, but not limited to these examples, withintegrated temperature and pressure mapping sensors, that synchronizesdata with a screening and pattern recognition algorithm. This algorithmassesses a PU risk score based on individual patient parameters and along-term real-time recording of how pressure and temperature have beendistributed in the patient's body. In an embodiment, a device includes asubstrate having a contact surface for contacting a user, one or moresacs associated with the contact surface of the substrate and containinga matrix of voxels. One or more sensors are incorporated in one or morevoxels, the one or more sensors adapted to measure changes in the one ormore voxels. The material is configured to be shock-absorbing andpressure-relieving such that the material is deformable by an action ofthe user contacting the contact surface causing the pressure in thematerial to be redistributed.

In an embodiment, a system includes (i) a device having a substratehaving a contact surface for contacting a user and one or more materialfilled sacs containing a matrix of voxels and associated with thecontact surface of the substrate, (ii) a controller configured totransmit and/or receive radio frequency signals to and from the one ormore sensors corresponding to the measured changes in the voxels, and(iii) a user feedback device in communication with the controller. Asubstrate having a contact surface for contacting a user, one or moresacs associated with the contact surface of the substrate, and one ormore sensors in communication with the one or more voxels, the one ormore sensors adapted to measure changes in voxels in the one or moresacs. The voxels contain a material configured to transmit pressure,temperature or humidity etc. The material is further configured to beshock-absorbing and pressure-relieving such that the material isdeformable by an action of the user contacting the contact surfacecausing the pressure in the material to be deformed. The user feedbackdevice configured to provide an indication to a user based on themeasured changes in one or more sensors.

In an embodiment, a system includes a patient wearable, example giving awrist band or an adhesive band placed on the skin, but not limited tothese examples, including one or several of the following functions (i)one or more RFID tags that are used to 3D location of the wearable (ii)One or sensors e.g. movement, heart-rate, temperature etc. and (iii) acontroller configured to transmit and/or receive radio frequency signalsto and from the one or more sensors corresponding to the measuredchanges, and (iiii) a user feedback device in communication with thecontroller, and (iiiii) patient ID. The patient wearable is to be pairedwith the patient and the patient device and patient station.

In an embodiment, a method includes measuring pressure, temperature orhumidity exerted by a portion of a subject's body on one or more sacscontaining a matrix of voxels associated with a substrate having acontact surface for contacting with the portion of the subject's body toprovide sensor information's and transmitting the information to areceiving station. The information indicates, using one or more ofaudio, visual, audiovisual, digital and/or haptic signal to the patientand the users.

In an embodiment, a method for monitoring and predicting of adverseevents, using changes in sensor data in conjunction with one or moresuitable prior information about the person or his/her behavior andconditions.

BRIEF DESCRIPTION OF DRAWINGS

In the present disclosure, reference is made to the accompanyingdrawings, which form a part hereof. In the drawings, similar symbolstypically identify similar components, unless context dictatesotherwise. Various embodiments described in the detailed description,drawings, and claims are illustrative and not meant to be limiting.Other embodiments may be used, and other changes may be made, withoutdeparting from the spirit or scope of the subject matter presentedherein. It will be understood that the aspects of the presentdisclosure, as generally described herein, and illustrated in theFigures, can be arranged, substituted, combined, separated, and designedin a wide variety of different configurations, all of which arecontemplated herein.

FIGS. 1a and 1b depict embodiments of a pressure monitoring deviceincorporated in a sock, in accordance with the principles and aspects ofthe present disclosure.

FIGS. 2a and 2b depict illustrative schematics of response of a devicesubjected to a local compressive load, in accordance with the principlesand aspects of the present disclosure.

FIGS. 3a and 3b depict embodiments of a pressure monitoring deviceincorporated in a shoe-sole that is controlled using a smartphone, inaccordance with the principles and aspects of the present disclosure.

FIGS. 4a and 4b depict embodiments of a pressure-monitoring deviceincorporated in mattress, in accordance with the principles and aspectsof the present disclosure.

FIG. 5 depicts a patient wristband together with mattress, where themattress can detect the 3D location and orientation of the wristband.

FIG. 6 depicts a pillow or wedge together with a mattress, where themattress can detect the 3D location and orientation of the pillow orwedge.

FIG. 7 depicts a seat with a backrest with a cloud service, inaccordance with the principles and aspects of the present disclosure.

FIG. 8 depicts an embodiment of a wireless pressure monitoring system,in accordance with the principles and aspects of the present disclosure.

FIG. 9 depicts an embodiment of a battery-less wireless pressuremonitoring system, in accordance with the principles and aspects of thepresent disclosure.

FIG. 10 depicts an embodiment with a radio frequency transmitter is alsoused a pressure sensor, in accordance with the principles and aspects ofthe present disclosure.

FIGS. 11a and 11b depict schematic drawings of sensors and wirelesstransmitter.

FIG. 12 depicts an illustrative process for a method of monitoring, riskestimating and predicting pressure ulcers using measurements (sensordata) such as from pressure, movement or temperature sensors incombination with one or more prior information about the person.

FIG. 13 depicts an illustrative pattern recognition model according toan embodiment.

FIG. 14 depicts a block diagram of a device used for analysis of sensordata in accordance with various aspects and principles of the presentdisclosure.

FIGS. 15a and 15b show embodiments of the system.

FIG. 16 depicts the person specific monitoring and feedback of the buildin sensors in various embodiments.

DETAILED DESCRIPTION

Before the present methods and systems are described, it is to beunderstood that this disclosure is not limited to the particularprocesses, methods and devices described herein, as these may vary. Itis also to be understood that the terminology used herein is for thepurpose of describing the particular versions or embodiments only and isnot intended to limit the scope of the present disclosure which will belimited only by the appended claims. Unless otherwise defined, alltechnical and scientific terms used herein have the same meanings ascommonly understood by one of ordinary skill in the art.

It must also be noted that as used herein and in the appended claims,the singular forms “a”, “an”, and “the” include plural reference unlessthe context clearly dictates otherwise. Thus, for example, reference toa “sensor” is a reference to one or more sensors and equivalents thereofknown to those skilled in the art, and so forth. Nothing in thisdisclosure is to be construed as an admission that the embodimentsdescribed in this disclosure are not entitled to antedate suchdisclosure by virtue of prior invention. As used in this document, theterm “comprising” means “including, but not limited to.”

Furthermore, reference to “prior information” is a reference to one ormore measurement(s), or observations about a person. Prior informationcould be observational data about hospitalized patient eating pattern,mobility level, physical activity level, mental activity level, state ofconsciousness, oedema, laboratory analysis age, gender, BMI orcomorbidities.

Disclosed herein are devices, methods and systems for monitoring anddetection of pressure or temperature on a part of a body of a user. Inan embodiment, a device includes a substrate having a contact surfacefor contacting a user, one or more sacs associated with the contactsurface of the substrate, and one or more sensors in communication withthe one or more sacs, the one or more sensors adapted to measure changesin pressure in the one or more sacs. The sacs contain a material, suchas a material, configured to transmit pressure. The material is furtherconfigured to be shock-absorbing and pressure-relieving such that thematerial is displaceable by an action of the user contacting the contactsurface causing the pressure in the material to be redistributed. Thematerial could be further subdivided into voxels to minimize shearstress between the patient skin and the system.

Disclosed herein are methods for monitoring and predicting of adverseevents, using changes in sensor data in conjunction with one or moresuitable prior information about the person or his/hers behavior andconditions. Embodiments disclosed herein also describe devices andsystems for implementing those methods and methods of use of suchdevices and systems. In various embodiments, devices and systemsdescribed herein may be used as part of other systems for prophylaxis,or treatment and/or alleviation of symptoms of a disease or aphysiological condition

In many embodiments, sensor data may be gathered for minutes, hours,days or even months prior to induction of the physiological event. Assuch, incidence of various features and patterns extracted from thesensor data may be correlated with the particular physiological eventbeing induced based on the analysis being performed.

In many embodiments the prior information's and sensor data collectedover hours/days/months is used in the pattern recognition algorithm toconstruct a user specific profile. As such, the user profile may begenerated by combining the sensor data from various pieces of personalfurniture e.g. a chair, a bed or pressure relieving aids.

In one embodiment the pattern recognition algorithm may detect changesto the user profile over hours/days/months in e.g. body temperature,weight or movement. And based on these changes the algorithm willcalculate a prediction of PU in minutes.

In one embodiment the pattern recognition algorithm may detect changesto the user profile over hours/days/months in e.g. body temperature,weight or movement. And based on these changes the algorithm willpredict an upcoming advance effect e.g. an increases in body weightincreases the risk for kidney and heart disease. While a decreases bodyweight over time (5% weight loss in 1 week) and decreases in bodymovement and increases in body temperature are signs of dehydration.

As used herein, the term “sensor” refers to a device that measures aphysical quantity and converts it into a signal, which can be read by anobserver or an instrument. In an embodiment, a pressure sensor may be adevice for measuring a pressure and converting it into an electricalsignal that can be read using an electronic instrument. In suchembodiment, a change in pressure results in an electrical signal or achange in an electrical signal that is correlated with the change inpressure, thereby providing a measure of the change in pressure. Thepressure measured by a pressure sensor may be absolute pressure orrelative pressure, e.g., pressure relative to atmospheric pressure.

Likewise, a temperature sensor may convert a temperature or a change intemperature into an electrical signal and a humidity sensor may converthumidity or a change in humidity into an electrical signal. The humiditymeasured by a humidity sensor may be absolute humidity or relativehumidity. In various embodiments, a sensor may need to be calibrated toprovide a meaningful measure. In some embodiments, a sensor may notconvert a measurement into an electrical signal.

Examples of pressure sensors include, but are not limited to, (i) straingauges wherein stretching of a lead wire leads to a measurable change inresistance of the lead wire; (ii) piezo-resistive sensors whereinresistance of the sensor material is sensitive to deformations anddisplacements; (iii) capacitive sensors wherein capacity of the sensoris measurably changed because a deformation causes a change in thedistance between the plates and/or the overlapping area of the plates(iiii) Force-resistant sensor wherein the resistance of the sensor ismeasureable changed because a deformation causes a change in force; andthe like.

As used herein, the term “voxels” is one or more equal or differentthree-dimensional volumes containing a “material” which can be a gas, aliquid, a gel, or a pressure-absorbing solid, e.g., foam. Examples ofmaterial include, but are not limited to, ethylene vinyl acetate,rubber, silicone rubber, Polyurethane rubber (PUR), neoprene, or air.One embodiment of the “material” is a “fluidic material.” Terms “sac,”“material sac”, or “material filled sac,” or “sac filled with material”are used interchangeably and refer to a cover, a cavity filled with amaterial such as a gas, a liquid, a gel, or a pressure absorbing solid.Embodiments of “sac,” “material sac”, or “material filled sac,” or “sacfilled with material” include “material sac,” or “material filled sac,”or “sac filled with material.” The material, such as fluid material,filled sac can be made from a textile fabric material such as, forexample, nylon, spandex, silk, wool, cotton, polyester, and the like, ora combination thereof. In other embodiments, the material filled sac canbe made from a pliable material such as, for example, rubber, plastic,silicone, neoprene and the like, or any combination thereof.

In some embodiments, the material in the material filled sac is chosensuch that excess pressure at a localized area of the sac isredistributed throughout the sac by displacement of the material,thereby relieving the pressure from the localized area. In someembodiments, the material in the material filled sac is chosen such thatexcess pressure at a localized area of the sac is redistributedthroughout the sac by displacement of the material, thereby relievingthe pressure from the localized area. Furthermore, such a sac filledwith a material, such as a fluid material, enables absorption anddissipation of sudden changes in pressure, thereby acting as ashock-absorber. As such, a sac filled with a material described hereincan act as a pressure-relieving and shock-absorbing device for a user.

In some embodiments, a plurality of material filled sacs in materialconducting communication with each other to form a network may be used.In some embodiments, independently sacs and voxels can be placed inmatrix and thereby minimizing shear stress e.g. when the patient movesin the bed. The material in such a network of material filled sacs mayredistribute pressure from a small localized area over a larger area,thereby relieving excess localized pressure. Furthermore, such a networkalso enables absorption and dissipation of sudden changes in pressure,thereby acting as shock-absorber. As such, a network of sacs filled witha material described herein can act as a pressure-relieving andshock-absorbing device for a user.

As used herein, the term “user” refers to a subject, human or animal,that uses the device or system disclosed herein. A user may be a personat risk for pressure ulcers such as, for example, a bed-ridden subject,a patient with neuropathy, a wheel-chair bound person, and the like. Insome embodiments, a user may be a subject suffering from pressureulcers.

Our pattern recognition algorithm is capable of integrating patientinformation both real-time information and history information topersonalize diagnosis of PU risk and keeps a long-term record ofpressure changes and temperature data that continuously inform thealgorithm regarding the real-time risk level of each individual patient.The diagnosis information provided by our solution (i) is continuouslyup to date, (ii) is sensitive to aggravation of risk factors (such astemperature increases), (iii) can be accessed by healthcareprofessionals in their current electronic patient record systems and(iv) enables the deployment of PU prevention strategies when they aremost needed, reducing inefficiencies of routine medical and nursingcare. Our approach not only increases the quality of life andindependence of bedridden patients, but also reduces the costs.

In one embodiment, the pressure relieving, and sensing mattress will bea two-dimensional array of around 200 individually working sensors builtinto the mattress structure, installable on a normal bed. The sensorswill be connected wirelessly, which makes them more prone to resist thenormal hospital use, addressing one of the barriers identified incompeting products. Each sensor is currently composed of a pressurechange measurement unit and a RFID tag or NFC tag. Each tag is capableof measuring temperature, collect the pressure data and communicatewirelessly all the information to a local storage unit. This collecteddata is continuously transmitted to our ICT backbone for analysis, usinga local wireless connection.

The pattern recognition algorithm combines multiples sources of datawhich contribute to more accurate and robust evaluations and prediction.Our algorithm combines data points from (i) the local electronic patientrecord system (e.g. BMI, age, edemas), (ii) the mattress continuous realtime data, and (iii) healthcare professionals' input using an improvedrisk measurement scale, based on the Braden or other scales (careprofessional can choose which one s/he prefers). The result of thesemultiple data points allowed us to vastly improve the riskstratification and enables prediction of adverse effect(s). Instead ofclassifying patients as low- or high-risk, our system predicts the riskevolution rate for each individual patient and alerts when it is time toimplement a preventive measure. Also, by mapping and analyzing thedistribution of the mattress pressures, we can determine the layingorientation of each patient, as well as detect s/he has moved. This isimportant because a patient that switches sides when lying in a bed isredistributing/alleviating the location of the pressures and thealgorithm reflects that change by readjusting the risk scores of eachbody part. Competing technologies require the nurse to manually reset atimer along with each postural change, while our solution willintelligently determine the best time frame to implement a personalizedpostural change, suggesting which body areas should be protected frompressure to alleviate the risk.

The smartphone app will communicate with the algorithm to enrich thecare experience. The caretaker's UI lets healthcare professionalsmonitor multiple patients, fill in the improved risk measurement scalefor each patient, see a schedule of intelligently predicted posturalchanges to be performed, and receive notifications when patients reachhigh risk assessments.

FIGS. 1a and 1b depict embodiment of a pressure monitoring deviceincorporated in a sock, in accordance with the principles and aspects ofthe present disclosure. Size of the sock 1 is adapted to the individualuser, so it fits comfortably. A pillow-like region forms the substrate 2and surrounds the underside and the front part of the foot of a user.FIG. 1a shows material filled sacs 3 are disposed in the pillow-likesubstrate and are configured to transmit the changes to various internaland external factors (e.g., pressure, temperature, humidity and thelike) to one or more sensors 4 disposed on the substrate. FIG. 1b is anembodiment wherein the material is a material in material filled sacs 3.

In some embodiments, the substrate 2 is made of thin, flexible,resilient and elastic textile product. Examples of materials that may beused for making substrate include, but are not limited to, nylon,spandex, silk, wool, cotton, polyester, and the like, or a combinationthereof. The contact surface of substrate 2 (the contact surface isshown by numeral 7 in FIG. 1b ) that engages or comes in contact withthe user's foot. Suitable permeability for water vapour andbacteriostatic properties are desirable for the material of the contactsurface so as to reduce risk of unwanted infections and for usercomfort. Material of contact surface 6 can be natural or syntheticfibres.

Associated with contact surface of substrate is disposed one or morematerial filled sacs 3 configured such that the material, which could amaterial, is displaceable between different sacs by an action, e.g.movement of the foot, of the user contacting the contact surface. Suchconfiguration allows for material pressure in the one or more sacs to beredistributed so as to dissipate and relieve excess pressure from alocalized portion of a user's body in contact with contact surface.

In various embodiments, material filled sacs 3 can be secured onportions of substrate by means of thermoweld, bonding, molding,laminating, sewing or any other suitable mechanism. In an embodiment,material filled sacs 3 have a meandering pattern. In some embodiments,material filled sacs 3 may be made of silicone, or similar compressiblematerial that is capable of redistributing pressure. In an embodiment, asurface of the material filled sacs coincides with the contact surface.

One or more sensors 4 may be disposed in communication with one or morematerial filled sacs 3. The sensors 4 may include, for example, pressuresensors, temperature sensors, humidity sensors, blood pressure sensors,and the like. In one embodiment, one or more pressure sensors aredisposed and secured inside one of material filled sacs 3. In anotherembodiment, one or more pressure sensors are disposed and secured on anouter surface of one of material filled sacs 3. In yet anotherembodiment, one or more pressure sensors are associated with contactsurface of substrate.

In some embodiments, one or more sensors 4 are connected to atransmitter or include a transmitter that can transmit the data measuredby one or more sensors 4 from the measurement area to a remote receiver5. Numeral 4 in the figures refer to sensor or the combination of sensorand transmitter. In various embodiments, the transmitter may usecommunication technologies such as, for example, Radio Frequencycommunication (RF), Near Field Communication (NFC), Bluetooth, Bluetoothlow energy (BLE), and the like.

In an embodiment, the transmitter is an RF transmitter. RF transmittersare widely used for uniquely identifying objects using radio frequencyelectromagnetic signals. Examples of uses of RF transmitter include, butare not limited to, inventory control, theft protection, monitoringtires pressure in cars, and the like. Typical RF transmitters use an RFIdentifier (RFID) which consists of transmitter (tag) for transmitting aunique identifier and other data to RF Readers, which are configured toreceive and decode data transmitted by the RFID. The tag is typicallycomposed of an antenna and a circuit to control a microchip. In someembodiments, the tag's microchip and antenna may both be used for themeasurement of pressure. An RF tag may be a passive tag or an activetag. A passive tag has no internal source of energy and therefore, maynot require any maintenance. A passive RFID tag is activated only whensending a specific radio signal. At such time the tag “wakes up” andtransmits a unique ID number and a characteristic measurable resistancewhich depends on the pressure of the material it is attached to.

In various embodiments, the RF transmitter may be disposed at a locationwhere it is not obstructive to the user and does not create pressurepoints. For example, the RF transmitter may be glued to a sole or sewninto a sock. In some embodiments, remote receiver 5 may be, for example,a bracelet, a mobile phone, remote control or the like. Remote receiver5, in some embodiments, may be configured to provide a feedback to theuser and/or a caregiver attending to the user. The feedback system canbe embodied with, e.g., colored light, to indicate when a foot issubjected to undesirable stresses. The remote receiver 5 is in contactwith other remote receivers 5 and connected wirelessly via a sharedserver 6.

In various embodiments, a RF transmitter itself may act as a pressuresensor a described elsewhere herein (in reference to FIG. 10). In suchembodiments, the RF transmitter may be placed directly at the measuringarea, e.g. at one of material filled sacs 3 as a direct pressure sensor,or in proximity as an indirect pressure sensor where the pressure signalfrom one area is being transmitted to the sensor via one or more otherareas.

In various embodiments, the system is composed of two separate devices.A force sensitive resistor film and a sensor TAG e.g. SL900A UHF RFIDsensor TAG from AMS embedded within a single flexible inlay. The TAG andantenna may be printed/mounted with e.g. glue directly on sensitiveresistor flexible film or maybe separate from the film with anon-conductive foil. The sensor TAG is composed of a microcontrollerwith built in NFC capabilities, built-in temperature sensor and aninterface for external sensors. The pressure sensor e.g. the forcesensitive resistor film can be seen as a variable resistor. When forceis applied the resistance changes. Because of this, the interface to themicrocontroller is a simple voltage divider.

In one embodiment material filled sacs 3 form a tree-like structurewhereby different sacs are in material conducting communication witheach other via the branches so that pressure changes can be transferredfrom a material filled sac in one area to one or more material filledsacs in another area via the branches. In some embodiments, materialfilled sacs 3 may be filled using a movable liquid or gel which, inaddition to transferring the pressure changes, can also massage andsupport the blood circulation during operation. Such configurationprovides the advantage that any excess pressure affecting the contactsurface is distributed over a larger area, thereby minimizing itsdeleterious effects. The material in material filled sacs 3 can move andcan be used to measure the pressure or change in pressure using one ofor more sensors 4. In embodiments with a transmitter, and a remotereceiver, measurements of pressure or change in pressure are furthertransmitted to the remote receiver via the transmitter.

In one embodiment material filled sacs may consist of different materialwhich is optimized for different part of the body.

FIG. 2a depicts an illustrative schematic of response of a devicesubjected to a local compressive load, in accordance with the principlesand aspects of the present disclosure. The sac is subdivided into amatrix of voxels. FIG. 2 depicts suppression by a local compressive loadof one of these voxels. And FIG. 2 depicts schematically depicts how thepressure changes (both static and dynamic changes) in the material inmaterial filled sac 3 propagate to one or more sensors 4. The sensortransmits data to a remote receiver 5, which may be in contact withother remote receivers 4 and connected wirelessly via a shared server 6.

FIG. 2b depicts an illustrative schematic of response of a devicesubjected to a local compressive load, in accordance with the principlesand aspects of the present disclosure. 201 depicts a schematic drawingof material filled sac 3 is shown. 202 schematically depicts the effectof subjecting material filled sac 3 to a local compressive load. 203schematically depicts how the local compressive load is quicklyeliminated by the pressure being dispersed to the entire material. 204schematically depicts that the material used to fill material filled sac3 is resilient and can expand if necessary. 205 schematically depictshow the pressure changes (both static and dynamic changes) in thematerial in material filled sacs propagate to one or more sensors 4.

FIG. 3a depicts an embodiment of a pressure monitoring deviceincorporated in a shoe-sole is controlled using a smartphone, inaccordance with the principles and aspects of the present disclosure.The shoe sole 31 acts as the substrate. Sensors 4 are placed on theunderside of the shoe sole. Numeral 5 depicts an example of a remotereceiver and numeral 6 depicts a collecting server and/or cloud service.

FIG. 3b depicts an embodiment of a pressure monitoring deviceincorporated in a shoe-sole is controlled using a smartphone, inaccordance with the principles and aspects of the present disclosure.The shoe sole 302 acts as the substrate. Sensors 304 are placed on theunderside of the shoe sole. Numeral 305 schematically depicts an exampleof user interface for a remote receiver in the form of a smart-phone.

In various other embodiments, substrate may be an article in contactwith a user's body. Examples of substrates include, but are not limitedto, sheets, mattresses, in-soles of shoes, socks, gloves, seat cushions,seat covers, and the like. A skilled artisan will be able to contemplateother embodiments of pressure monitoring devices in accordance withvarious principles and aspects of the present disclosure.

For example, FIG. 4a depicts an embodiment of a pressure monitoringdevice wherein the substrate is a sheet (or a mattress cover). 3schematically depicts an example of placement of material filled sacs. 4Numeral depicts different antennas (sensor/transmitter) detecting the 3Dlocation and orientation of the remote receiver 5, which in turntransmits data wirelessly to the cloud 6 which could comprise a sharedserver. Numeral 46 schematically depicts a matrix of voxels, which eachsac is subdivided into, and an example of placement of sensors below/ineach voxel. Other components of the pressure monitoring device may besuitably placed by one skilled in the art in accordance with variousaspects and principles disclosed herein.

FIG. 4b depicts an embodiment of a pressure monitoring device whereinthe substrate is a sheet (or a mattress cover). Numeral 403 is anexample of placement of material filled sacs. Numeral 404 schematicallydepicts an example of placement of sensors. Other components of thepressure monitoring device may be suitably placed by one skilled in theart in accordance with various aspects and principles disclosed herein.

One advantage of such a device is that the sensors and associatedelectronics may be located visibly, hidden away from the measurementarea, or can be removable. This means that the sensors and associatedelectronics can be removed, to facilitate cleaning, including themachine-washing of the device.

In one embodiment, a pressure monitoring system may include a devicecomprising: (i) a substrate having a contact surface for contacting auser; (ii) one or more material filled sacs associated with the contactsurface of the substrate, and (iii) one or more sensors in communicationwith the one or more material filled sacs. The sacs contain a materialconfigured to transmit pressure. The material is further configured tobe shock-absorbing and pressure-relieving such that the material isdisplaceable by an action of the user contacting the contact surfacecausing the pressure in the material to be redistributed. The one ormore sensors are adapted to measure changes in pressure in the one ormore material filled sacs. The one or more sensors are in communicationwith at least one transmitter adapted to transmit a measurement by theone or more sensors. The system further includes a controller configuredto transmit and/or receive signals to and from the one or more sensorscorresponding to the measured changes in pressure, and a user feedbackdevice in communication with the controller. The user feedback device isconfigured to provide an indication to a user based on the measuredchanges in pressure.

In some embodiments, the at least one transmitter is adapted to transmitwireless signals using technologies such as, for example, RadioFrequency communication (RF), Near Field Communication (NFC), Bluetooth,Bluetooth low energy (BLE), and the like. The controller is adapted totransmit and/or receive signals compatible to the transmitter.

A receiver containing electronics and user feedback device as display,speakers, and/or an LED light need not be placed on the substrate. Thesecan be placed anywhere on the user interface device or used in theimmediate vicinity of the substrate, thereby avoiding placement of hardmaterials at sites that have high risk of forming pressure ulcers.Additionally, the signal and the power cable may be completely avoidedby the sensors and electronics to wirelessly transmit data from therecorded measurement range to the remote receiver, which can be placedat a place on the device or in the vicinity of the latter.

In various embodiments, the user feedback device may be configured toprovide an indication or an alert to a user and/or a caregiver attendingto the user if the pressure information indicates a pressure in excessof a pre-determined threshold and/or for duration longer than apre-determined period of time. The threshold pressure and period of timemay be determined by the user and/or the caregiver based on factors suchas, for example, age, sex, weight, blood pressure, and/or other factorsrelating to the user that determine the user's risk of contractingpressure ulcers.

FIG. 5 depicts a patient wristband 5, which can be detected in 3Dorientation and 3D location in relation to the mattress 51 by the buildin antennas 4 in the mattress 1.

FIG. 6 depicts a pillow or wedge 63, which can be detected in 3Dorientation and 3D location in relation to the mattress 61 by the buildin antennas 4 in the mattress 61. The pillow or wedge has built-insensors, which are communicating wirelessly with the receiver in themattress 61.

FIG. 7 depicts a seat and back-rest 71 with build in sensors/transmitter4 like the mattress in FIG. 4a , able to communicate wirelessly with asmartphone/receiver 5 and further with a cloud service 6.

FIG. 8 depicts the flow of signals in a wireless pressure monitoringsystem, in accordance with the principles and aspects of the presentdisclosure. The embodiment depicted in FIG. 5 includes a temperaturesensor to account for pressure changes due to temperature changes. At501 temperature and pressure data is measured using one or more sensors.This data is encoded and preprocessed at 502 and delivered to the RFtransmitter at 503. At 504, the antenna of the RF transmitter transmitspre-processed pressure and temperature data as an RF signal which isreceived, at 505, by the antenna of the RF receiver. The RF receiver, at506, delivers the signal to the controller. At 507, the controllerdecodes the pressure and temperature data, performs additional signalprocessing (if required) and delivers it to the user feedback device. At508, the user feedback indicates the temperature and pressure data tothe user.

In various embodiments, the controller and the user feedback device maybe incorporated in a single device such as, for example, a smartphone, alaptop computer, a tablet computer, a dedicated handheld device, and thelike. The user feedback device may indicate a feedback using, forexample, audio, audiovisual, visual, or haptic signals.

Various portions of electronics used in the system of the embodimentdescribed with respect to FIG. 8 may be powered using an internalbattery. For example, a battery may be disposed in one of the materialfilled sacs and be connected to the one or more sensors and the RFtransmitter. The energy required for preforming the pressure and/ortemperature measurements (as well as other measurements whereapplicable) as well as for encoding and pre-processing the measurementdata may be provided by such a battery. Furthermore, such a battery mayalso provide energy required by the RF transmitter for transmitting thepressure and temperature data (as well as other data where applicable).Such embodiments may provide continuous real-time data from themeasurements. However, such embodiments may be limited in time of use byfailure of the internal battery which may need to be replacedperiodically and may increase the operating costs. In some otherembodiments, a connection lead (not shown) may be provided to the sensorand/or the RF transmitter from outside the substrate. This connectionlead may be used to provide energy (using a battery or any other sourceof electricity). In yet other embodiments, the system may be modified towork without an internal battery.

In one embodiment, as depicted in FIG. 9, the system lacks an internalbattery used to power the sensors and the RF transmitter. In such anembodiment, the one or more sensors are connected to an RF transceiverwhich is enabled to harvest energy from a received RF signal. Thisenergy is used to power the sensor(s) to allow the sensor(s) to performthe desired measurements. Alternatively, such an embodiment may use apassive RF tag.

FIG. 9 depicts an embodiment of a battery-less wireless pressuremonitoring system, in accordance with the principles and aspects of thepresent disclosure. At 608, a user or a caregiver requests, through theuser feedback device, for pressure and/or temperature data. The requestis transmitted through the controller, to the RF transmitter (through607, 606, 605, and 604, indicated by arrows pointing left). At 603, theRF transceiver harvests energy from the signal it receives and powersthe encoder and the sensor(s) (as indicated by the arrows pointing leftand labeled power). At 601 temperature and pressure data is measuredusing one or more sensors. This data is encoded and preprocessed at 602and delivered to the RF transmitter at 603. At 604, the antenna of theRF transmitter transmits pre-processed pressure and temperature data asan RF signal which is received, at 605, by the antenna of the RFreceiver. The RF receiver, at 606, delivers the signal to thecontroller. At 607, the controller decodes the pressure and temperaturedata, performs additional signal processing (if required) and deliversit to the user feedback device. At 608, the user feedback indicates thetemperature and pressure data to the user.

FIG. 10 depicts an embodiment with a radio frequency transmitter is alsoused a pressure sensor, in accordance with the principles and aspects ofthe present disclosure. In an embodiment, a pressure sensor consists ofone or more of the passive or active RF tags that can be embedded in amaterial filled sac for radio communication and for measuring bothstatic and dynamic pressure changes. When load on the material filledsac increases, the antenna embedded in the material filled sac getsstretched resulting in a change in the antenna's detectable complexresistance. This can be used to measure the change in pressureexperienced by the material filled sac.

The devices and systems described herein open new possibilities for aperson to monitor problem areas on the body continuously in his dailylife, which in turn opens up new opportunities for long-term monitoringof chronic wounds.

FIG. 11A depicts schematic drawings of the construction of sensors withwireless transmitter. The upper layer is a resistive polymer 111 gluedon space layer(s) 112 and onto the lower layer 113 with electrodes 114connected to antennas 115 and a transmitter/sensors 116.

FIG. 11B depicts a variation of 11A with antennas 115 andtransmitter/sensors positioned on the upper resistive polymer layer 111.

FIG. 12 depicts an illustrative process for a method of monitoring andpredicting a pressure ulcer using sensor data in combination with one ormore prior information according to an embodiment. At block 110, priorinformation of a subject is obtained. The prior information fed to aprocessor P which, at block 150, analyzes the data based on apre-determined algorithm. At block 130, processed data is combined(using, e.g., another processor not shown in FIG. 1) with measurementsrelating to sensor data from one or more sensors gathered at block 120and analyzed for change in risk of pressure ulcers. This analysis may befed back to processor P for analysis at block 150. If the change in riskof pressure ulcers is deemed, based on a pre-determined set of criteria,a reaction R is provided at block 175.

Sensor data of a subject may be measured using any device or method. Forexample, in an embodiment, Sensor data of a subject is measured usingpressure sensors. FIG. 10 depicts an illustrative pattern recognitionmodel according to an embodiment. In various embodiments, analysis ofSensor data at block 150 may include, for example in FIG. 13,preprocessing at block 210, feature extraction at block 220, featurereduction at block 230, and classification or risk estimation at block240.

In embodiments where sensor data is measured using a pressure sensor, asignal from the pressure sensor is preprocessed, at block 210, forremoval of noise and uninformative information.

Preprocessing of the sensor data from the pressure sensor may befollowed by feature extraction, at block 220. Preprocessed data is sentto block 220 to find, preferably, a small number of features that areparticularly distinguishing and/or informative for classification and/orrisk estimation of pressure ulcer. Features may be mathematicalderivative from the sensor data from any interval in obtained data.

Analysis performed on the sensor data at block 220 may, in variousembodiments, include, for example, differentiation, averaging,calculation of slope, ratios of instantaneous values, standarddeviation, skewness, regression coefficients, slopes of regressionratios, and standardized moment, and so forth. Features extracted fromthe sensor data may include, for example, median pressure data fromparticular epoch range prior to an event occur, or the skewness ofpressure data particular epoch range prior to an event, and so forth.

Sensor data extracted at block 220 may include a large number ofdifferent features may be evaluated for their ability to predictpressure ulcer. Such features may then, be passed down to block 230 tobe grouped to form patterns that may be indicative of a pressure ulcerevent. At block 230, a ranking algorithm based on e.g. a t-test or ROCmay be used, in some embodiments, for eliminating features that do notsignify an event prediction.

In some embodiments, the ranking algorithm may calculate an averageseparability criterion for each feature. Such a criterion may reflectthe ability of the classification method to separate the means of anytwo classes of features in relation to the variance of each class.Subsequently, various features may be correlated with physiologicalevents. Features with lowest separability may be eliminated ifcorrelation with higher ranking features exceeds a threshold. In anembodiment, a correlation threshold of, for example, 0.7 may be used. Invarious embodiments, the correlation threshold may be chosen dependingon the desired specificity and sensitivity of prediction of thephysiological event. In many embodiments, cross-validation may beperformed to reduce generalization errors.

Once the features are extracted and reduced, particular features may bechosen for their ability to predict pressure ulcer(s). This is followedby classification/risk estimation, at block 240, of the features tocorrelate them with pressure ulcer. Various classification models maythen be used for classifying a future point in time as normal (nopressure ulcer) or abnormal (pressure ulcer) based on such features. Forexample, in an embodiment, non-probabilistic binary linear classifiersupport vector machine may be used. A skilled artisan will appreciatethat other classification methods may be also used, alone or incombination. For example, linear classifier models such as Fisher'slinear discriminant, logistic regression, naive Bayes classifier,Perceptron, may be used for classification/risk estimation. Otherexamples of classification models include, but are not limited to,quadratic classifiers, k-nearest neighbor kernel estimation, randomforests decision trees, neural networks, Bayesian networks, HiddenMarkov models, Gaussian mixture models, and so forth. In someembodiments, multi-class classification/risk estimation may also beused, if needed.

In an embodiment, at block 240, forward selection may be used to selecta subset of features for optimal classification. This selection may beperformed by including a cross-validation with, for example, 10 groupsand allocating a particular number of events for training the model.Forward selection may start with no features followed by assessing eachfeature to find the best feature that correlates with the particularphysiological event. Such feature may, then, be included in an optimalfeature subset for appropriate classification. Selection of new featuresmay be repeated until addition of new features does not result inimproved predictive performance of the model.

FIG. 14 depicts a block diagram of a device used for analysis of sensordata in accordance with various aspects and principles of the presentdisclosure. Device 300 used for analysis of sensor data may includeprocessor 310 configured to run algorithm 320 that enables prediction ordetection of a pressure ulcer. Sensor data 350 along with at least oneprior information 375 and their time of measurement are received andanalyzed by algorithm 320. In some embodiments, measurements of sensordata 350 and prior information 375 may be entered manually. In otherembodiments, the measurements may be transmitted automatically toprocessor 310 using a wired or a wireless connection to device 300.Algorithm 320 may include, calculating one or more statisticalmeasures/mathematical derived measures, at block 322, of sensor data 350and prior information 375 data. At block 324, the risk of pressure ulceris estimated and analyzed for a possibility that one or more pressureulcer(s) may develop. At block 326, an output is generated based on theanalysis of block 324. For example, if it is determined, at block 324,that the risk is predominant, an alarm signal is generated at block 326.Device 300 may produce a reaction 340 based on the output generated atblock 326. In various embodiments, reaction 340 may be a visual, audio,or audiovisual signal such as, for example, an alarm, a text message, aflashing light, and so forth.

In many embodiments, processor 310 may be part of a computer, a tablet,a smartphone, server application, web application, or a standalonedevice. In some embodiments, the device may have in-built sensors formeasuring sensor data 350. In many embodiments, the device used foranalyzing the sensor data may include, for example, a controlling unit(e.g., a digital signal processor or DSP), a memory (e.g., random accessmemory, and/or non-volatile memory), one or more sensors (e.g., IRsensors, electrodes, etc.), one or more feedback mechanisms (e.g.,display, a printer, speakers, LEDs or other light sources, etc.), and/orone or more input ports.

In an embodiment, sensor data 350 may be combined, at block 322, withobservational information about a subject 375 for monitoring andprediction of pressure ulcer. In such embodiments, with observationalinformation 375 may be combined with, e.g., pressure, movement andtemperature measurements 350 taken over a period prior to a discoveredpressure ulcer. Patterns from the combination of sensor data andobservational information may be used risk estimate the occurrence ofpressure ulcer.

In an embodiment, FIG. 15a , the system is used in a hospital toestimate the risk of a particular patient's risk of developing apressure ulcer. Pressure, movement and temperature sensors are embeddedin a mattress placed underneath the patient. Sensor data from themattress are sent every minute by a wireless connection to a server(backend). The server obtains prior information about the patient suchas the patient eating pattern, mobility level, physical activity level,mental activity level, state of consciousness, oedema, age, gender, BMIor comorbidities. The sensor data and prior information are thenanalyzed as previously described hereby outputting risk estimation forthe patient to develop a pressure ulcer within the next day or two. Therisk estimation and other relevant information are directly sent torelevant caretakers at the hospital. In this embodiment the riskinformation is send to the caretaker's mobile phone. At the bases of therisk estimation, the caretakers can take measure to prevent thedevelopment of a pressure ulcer.

In an embodiment, FIG. 15b , show how the combination of sensors andpattern recognition algorithm a used to construct a person specific riskprofile A) New Patient enters the hospital or nursing home and riskassessment is done by the PU screening algorithm tool called Q-scale.Depending on the risk assessment outcome the patient either continues asis by A-1) in B) with no PU risk or very low PU risk in the same bedwithout any further PU attention nor PU prevention aid. Or with eithermoderate or high PU risk by A-2) to C) A bed with a multi sensormattress which is supporting different repositioning schemes andprevention aim C-1, C-2 and C-3 as well as communicating data with D) asmartphone app or other user interface. If patient movement areregistered by the sensors mattress the Q-scale will automaticallyperform a new re-assessment of the PU risk using the Q-scale and C-1)upload new recommended PU prevention scheme and treatment with differentrepositioning timeframes in either the app for healthcare personal whichmight or might not be integrated in the EPJ, (Electronic PatientJournal) or C-2) if possible prompt the patient for repositioning withaudio and light notifications through e.g. LED and buzzer sounds on orin the Q-bed mattress. Or C-3), patient reposition is performedautomatically with robot or mechanical aided. E.g. supplementing to thisinvention with the automated third party self-turning beds, which arealready on the market, or programmed robots revealing the health carepersonnel's need for attention and/or labor heavy workload. Especiallypatients with high PU risk and oversize patients are extremely laboredextensive in repositioning with demands for heavy and fragile lifting.The pattern recognition algorithm in combination with the sensormattress will over a period of time construct a user specific profileand automatically re-address the PU risk assessment e.g. detect changesto the user profile and by D-1) at least every 24 h and the results ofthe Q-scale may change the risk assessment into new time intervals ornew PU prevention schemes and treatment.

FIG. 16 depicts various embodiments like a wristband 162, a pillow 162,a mattress 163, a seat-rest 164, a sock 165 and shoe soles 166communicating wirelessly with a receiver/smartphone/tablet 167. Thescreening and monitoring algorithm is providing a prediction personspecific risk with feedback to patient and healthcare personal.

In an embodiment, a method of monitoring pressure on a portion of auser's body may include measuring pressure exerted by a portion of asubject's body on one or more material filled sacs associated with asubstrate having a contact surface for contacting with the portion ofthe subject's body to provide a pressure information, and transmittingthe pressure information to a receiving station. The pressureinformation is used to indicate a pressure in excess of a predeterminedthreshold using one or more of audio, visual, audiovisual or hapticsignal.

The predetermined threshold may be set by the user and/or the caregiverdepending on the age, sex, weight, blood pressure, and/or other factorsof the user that determine the user's risk of contracting pressureulcers. Alternatively, a caregiver may provide such recommendation basedon such or other factors deemed relevant by the caregiver.

In various embodiments, the method may be executed using the devices orsystems described herein. For example, measuring pressure exerted by auser's foot may be performed using the sock described herein.Furthermore, the sock may also be used to transmit the pressureinformation to the controller or a receiving station of a systemdescribed herein. Likewise, in other embodiments, a user feedback deviceof a system described herein with reference to FIG. 8 may provide theuser and/or caregiver with an indication about the excess pressure onportions of a quadriplegic patent's back.

The foregoing detailed description has set forth various embodiments ofthe devices and/or processes by the use of diagrams, flowcharts, and/orexamples. Insofar as such diagrams, flowcharts, and/or examples containone or more functions and/or operations, it will be understood by thosewithin the art that each function and/or operation within such diagrams,flowcharts, or examples can be implemented, individually and/orcollectively, by a wide range of hardware, software, firmware, orvirtually any combination thereof.

Those skilled in the art will recognize that it is common within the artto describe devices and/or processes in the fashion set forth herein,and thereafter use engineering practices to integrate such describeddevices and/or processes into data processing systems. That is, at leasta portion of the devices and/or processes described herein can beintegrated into a data processing system via a reasonable amount ofexperimentation.

The herein described subject matter sometimes illustrates differentcomponents contained within, or connected with, different othercomponents. It is to be understood that such depicted architectures aremerely exemplary, and that in fact many other architectures can beimplemented which achieve the same functionality. In a conceptual sense,any arrangement of components to achieve the same functionality iseffectively “associated” such that the desired functionality isachieved. Hence, any two components herein combined to achieve aparticular functionality can be seen as “associated with” each othersuch that the desired functionality is achieved, irrespective ofarchitectures or intermediate components.

With respect to the use of substantially any plural and/or singularterms herein, those having skill in the art can translate from theplural to the singular and/or from the singular to the plural as isappropriate to the context and/or application. The varioussingular/plural permutations may be expressly set forth herein for sakeof clarity.

All references, including but not limited to patents, patentapplications, and non-patent literature are hereby incorporated byreference herein in their entirety.

While various aspects and embodiments have been disclosed herein, otheraspects and embodiments will be apparent to those skilled in the art.The various aspects and embodiments disclosed herein are for purposes ofillustration and are not intended to be limiting, with the true scopeand spirit being indicated by the following claims.

EXAMPLES

Embodiments illustrating the devices, methods and systems describedherein may be further understood by reference to the followingnon-limiting examples:

Example 1: Prediction of in-Hospital Pressure Ulcer Development—ClinicalValidation Study

Several risk scores assessing the patient's risk of developing PU havebeen proposed and used in medical care such as the Braden, Waterlow andNorton scale. However, the predictive values of these scales have shownlow to modest accuracy. We hypothesize that PU can be prevented bydedicated early warning in high risk patients. Therefore, weinvestigated a new model for In-Hospital prediction of PU development.

Study design: Patients were recruited from March 2011 to September 2011.The included patients were observed from admission until discharge date.Data were collected by three research nurses, one located in each of theparticipating wards. The three nurses were all specialized in observingskin conditions indicative of PU development, in scientific datacollection, and in preventive care. Participants: Patients aged 20 yearswere included in the study if they were admitted in one of threeparticipating wards. Patients admitted and discharged within the samedate were excluded from the study. Moreover, patients with PU atadmission were excluded.

Data measurements: Data were obtained on the day of admission, the dayafter the admission, and every fourth day until discharge. Data werecollected from patient medical files and by dedicated observations ofeach patient. Data included information on outcome, risk factors, and PUprevention activities.

Model derivation and development: A pattern classification method wasdeveloped to predict individualized development of PU into one of twoclasses: (1) no PU during hospitalization or (2) development of PUduring hospitalization.

Logistic regression classification was chosen for foundation of themodel due to the possibility of including both nominal and ordinal datatypes. Logistic regression utilizes a transparent decision model—thismakes it attractive in a clinical setting as a decision support system.We used forward selection to include features in the model based onstatistical significance. Moreover, we used 10-fold cross validation toensure that the model was not over-fitted and that the results weretransferrable to a similar cohort. We derived and tested the model on arotating 9 (of 10) partitions of training data and 1 (of 10) partitionsof test data. The accepted statistical methods ensure valid testing ofthe model performance and reduce generalization bias.

Validation and comparison: We evaluated the prediction models throughsensitivity and specificity for pre-determined cutoff points andreceiver operating characteristics (ROCS) based on logistic regressionmodels comparing the area under the curve (AUC) of the new model.

We used another cohort for validation (N=131); this data was obtained inthe same manner as the training cohort and also from the AarhusUniversity Hospital. In the validation cohort data scoring on the Bradenscale were also obtained in these patients. We also compared our resultswith that of using the Braden scale for predicting the development of PUduring hospitalization.

Results: A total of 383 patients were included in this study. Thetraining data included 252 patients and the validation data included 131patients. In the training data the mean age was 63 (.+−.SD 16) years,36% were women, 30% of the patients were recruited from a medical unit,51% from a Surgical unit, 19% from an Intensive Care unit. Furthermore,we observed a pressure injury incidence of 12.7%. In the validation datathe mean age was 65 (.+−. SD 16) years, 34% were women, 35% of thepatients were recruited from a medical unit, 47% from a Surgical unit,and 18% from an Intensive Care unit. The observed incidence for pressureinjuries was 26.7%.

The training data yielded an area under the curve (AUC) of 0.82, the AUCof the validation data was also 0.82. The Qscale had a significantlyhigher AUC compared to that of the Braden scale with an AUC of 0.76(p<0.05). When comparing the performance at specific thresholds for thelow threshold, a specificity of 94% and a sensitivity of 47% was found(table2). This was significantly (p<0.05) better than the Braden scorewith a specificity of 94% and a sensitivity of 20%.

We tested a new scale for predicting PU using only simple observationaldata and gender of the patient. The new scale which combinesobservational and on-site available information regarding patientmobility, willingness and motivation could lead to an improved accuracyin predicting PU compared with a well-established method. The Bradenscale is the most widely used risk scale in Denmark and therefore usedfor comparison in this study. For a threshold with a high specificity of94% the new scale could improve the sensitivity significantly from 20%to 43% (Braden-scale vs Qscale). This means that the Qscale canpotentially predict 43% of developing PU with few false positive. Inclinical use a higher sensitivity could be chosen on the cost ofspecificity. This calculation of an optimal sensitivity and specificitywould require a cost-benefit analysis which includes the cost oftreating patients predicted to develop ulcers (true positives and falsepositives), the potential benefit such as reduced development of ulcersand savings. Moreover, this sensitivity of 43% would yield a positivepredictive value (PPV) of 72% and a negative predictive value (NPV) of92%. In other word this would mean that the clinicians would have totreat 10 patients and 7 of these would develop PU if no preventivemeasures were taken. Of course, the PPV is influenced by the incidencefor having PU in a specific cohort. For instance, we observed adifference in the PPV between the training and validation results. Thiswas primarily due to the differences in incidence rate between the twosamples. In the training data we observed an incidence rate of 12.7% forthe development of a PU—in the validation data we observed an incidencerate of 26.7%. Several studies have shown how the prevalence/incidenceis varying between departments, this could explain the difference inincidence between the training and validation data.

The implication of identifying patients prone to developing PU during ahospital stay is to enable clinicians to target these patients with apersonalized prevention plan. Patients with a high risk of PU could betreated with friction-reducing mattresses and an intensified plan forhelping the patient to move or be mobilized during day and night. On theother hand patients with low risk of developing pressure ulcers mightnot need same level of attention for preventing PU and these patientscould be checked less intensively. As described, significant resourcesare being used on treating pressure ulcers each year 5. If just a smallpercentage of these iatrogenic wounds could be avoided the hospitalswould save significant resources. But this would also be of greatbenefit for the patients, who often suffer severely as a result of thesecomplications. One potential usage of the proposed score could be thatpatients with a high risk of developing PU could receive intensiveprevention measures. Such measures could include more frequentobservations and assistance to change body position. Another mean couldbe to use a pressure-relieving sensor mattress.

Our proposed model did show a high AUC of 0.82, and this was alsoobserved in the validation sample. However, we know that the conditionsfor these patients are varying from hospital to hospital and from unitto unit. We did include different types of units and validated the modelon new data. Another perspective to improve the performance of thesemodels would be to include additional hospital obtained data on thepatient status. This could be results from blood samples, temperaturemeasurements or skin pressure measurement (if the patients are using apressure sensitive mattress). These data could be merged with theobserved state of the patient to enhance the overall representation ofthe patient's ability to move and hereby also reduce the risk ofdeveloping PU.

We used logistic regression as a model basis. Logistic regression isoften used in population modeling because population growth oftenfollows a logistic-curve. Also, the results are easy to interpret. Butit is possible that non-linear methods such as Decision tree orK-nearest neighbor may improve accuracy as these classifiers have beenshown to produce reliable results in other applications.

In conclusion, we have developed and investigated a new algorithm toidentify patients at risk for developing pressure ulcers duringhospital-admission. Our study showed promising results on both thetraining, the validation data and in comparison, to the Braden scale.The new Qscale could be used in the prevention of PU in a hospitalsetting

Example 2: A Sock for Wirelessly Monitoring Pressure on a Foot

FIG. 1 shows a sock for wirelessly monitoring pressure on the foot of apatient. The sock can be made from a suitable textile fabric materialsuch as nylon, spandex, silk, wool, cotton, polyester, and the like, ora combination thereof. A cushioning case or a pouch is stitched to theunderside of the sock. The case or pouch is shaped to match the shapethe underside of the sock such that a user's foot is completelycushioned by the pouch when the user wears the sock. The pouch is madefrom substantially the same textile fabric material as the sock.Material filled sacs made of silicone and filled with air are placedinside the pouch. The material filled sacs are provided in a meanderingpattern (refer to FIG. 1) such that substantially the entire undersideof the user's foot resides on at least a portion of the meanderingpattern at all times while the user is wearing the sock.

An RF antenna acting as a pressure sensor is placed on the underside ofone of material filled sacs such that the pressure sensor residesdirectly under heel of the user. A removable battery is provided forpowering the RF antenna. The battery may be placed away from theunderside of the foot, for example, in the sock near the ankle of theuser. A wired connection may be provided from the battery to the RFantenna. A software application (App) on a smartphone communicates withthe RF antenna to provide the user with a measurement of pressure on thefoot on which the sock is worn. The App is configured to alert the userif the pressure is higher is normal for an extended period of time.

Example 3: Monitoring Pressure on a Foot of a Patient

A patient suffering from diabetic peripheral neuropathy in her feet isprovided with a sock of Example 1. When the patient wears the sock, thematerial filled sacs act to cushion the foot of the patient on which thesock is worn. When the patient is in a position which exerts excesspressure on a portion of the foot, the material filled sacs under thatportion of the foot redistribute the pressure throughout the surface ofthe foot. Additionally, the RF antenna and the pressure sensor measurethe change in pressure and transmit to the smartphone applicationprovided to the patient. The smartphone application alters the patientabout the excess pressure, prompting her to change the position of herfoot.

Example 4: A Sheet for Wirelessly Monitoring Pressure on the Backside ofa Bed-Bound Patient

FIG. 8 shows a working prototype of a sheet for wirelessly monitoringpressure on the back of a bed-bound patient, e.g., a comatose patient ora quadriplegic patient. The sheet consists of 4 distinct compartments(811-814). Each of the compartments can be made from a suitable textilefabric material such as cotton, polyester, and the like, or acombination thereof. The sheet has a length and width sufficient toextend along substantially the entire back portion of a bed-boundpatient, i.e., from head to feet, such that a patient lying with theirback down would cover at least a portion of the sheet. The compartmentsmay be sized such that the patient's head and neck rest on compartment811, the patient's upper back rests on compartment 812, the patient'slower back and hind-quarters rest on compartment 813, and the patient'slegs rest on compartment 814. Inside each compartment is placed a pouchcontaining material filled sacs filled with silicone. The materialfilled sacs are provided in a meandering shape. The pouch extendssubstantially the entire length and width of each of the compartments.

An RF antenna acting as a pressure sensor is placed substantially at thecenter of each of the pouches inside and under the material filled sacs.A removable battery or other similar power source is provided forpowering the RF antenna. The battery may be placed away from the portionof the compartment that is contact with the body of the patient. A wiredconnection may be provided from the battery to the RF antenna. Asoftware application on a bedside monitoring device communicates withthe RF antenna to provide the patient and/or a caregiver with ameasurement of pressure on backside of the patient. The softwareapplication is configured to alert the patient and/or the caregiver ifthe pressure is higher is normal for an extended period of time.

Example 5: Monitoring the Pressure on the Backside of a Bed-BoundPatient

A comatose patient is provided with a sheet of Example 3. The patientlays backside-down on the sheet such that the material filled sacs actto cushion the backside of the patient. When the patient is in aposition which exerts excess pressure on any portion of the patient'sbody resting on one of the compartments, e.g., a portion upper back nearthe scapula, the material filled sacs under that portion of the bodyredistribute the pressure throughout compartment on which that portionrests. Additionally, the RF antenna and the pressure sensor measure thechange in pressure and transmit to the smartphone application providedto the patient. If the pressure has not been relieved over apre-determined length of time, the smartphone application alters thecaregiver about the static excess pressure, prompting her to change thepatients' position.

Example 6: Risk Stratification of Patients

Preliminary analysis of clinical data on 134 patients show that it ispossible to stratify and predict which patients are at high risk fordeveloping pressure ulcers during hospitalization. There are alreadysimple scoring systems to risk stratify but as shown in the followingROC curve—which illustrate a model's ability to find the true patientswith wounds from the false-positive found patients—these scoring systems(Braden and the newly developed ADHOC) are not very accurate. The bluecurve shows that by using an algorithm that combines information aboutthe patient's condition, such as the ability and willingness to mobilizethemselves, physiological state, etc. it is possible to risk stratifypatients more intelligent. The initial analysis indicates that it couldbe possible to find 8 out of 10 patients with future ulcers and that thealgorithm had a false positive rate of about 15%. Furthermore, it ispossible with the algorithm to analyses multiple data pointssimultaneously both history and real-time. And Instead of classifyingpatients as low- or high-risk, our system predicts the time to onset ofPU for each individual patient and alerts when it is time to implement apreventive measure. Also, by mapping and analyzing the distribution ofthe real-time pressure and temperature measurements for the mattress, wecan determine the laying orientation of each patient, as well as detects/he has moved. This is important because a patient that switches sideswhen lying in a bed is redistributing/alleviating the location of thepressures and the algorithm reflects that change by readjusting the riskscores of each body part.

What is claimed is:
 1. A system comprising a resting device for restinga patient, the resting device comprising: a substrate having a contactsurface for contacting the patient, one or more sacs comprising amaterial and associated with the contact surface of the substrate, oneor more sensors that are incorporated in the one or more sacs, and apatient recognition algorithm to detect changes in a user profile;wherein the system is configured to at least (a) combine information andconstruct the user profile, wherein the information comprises a firstdata from a pressure ulcer risk scale and a second data obtained via theresting device over time, and (b) automatically perform an assessment ofa risk of pressure ulcer in the patient.
 2. The system of claim 1,wherein the patient recognition algorithm is configured to at leastpredict the risk of pressure ulcer in the patient.
 3. The system ofclaim 1, wherein the system is further configured to predict the risk ofpressure ulcer in the patient using at least (a) sensor data obtainedfrom the one or more sensors and (b) one or more prior data of thepatient.
 4. The system of claim 3, further comprising one or moreprocessors that analyze the one or more prior data of the patient basedon a pre-determined algorithm and produce processed data.
 5. The systemof claim 4, wherein the one or more processors are configured to atleast (a) combine the processed data with the sensor data from the oneor more sensors and (b) determine a change in the risk of pressure ulcerin the patient.
 6. The system of claim 4, wherein the one or moreprocessors are configured to preprocess the sensor data obtained fromthe one or more sensors to generate preprocessed data and extract one ormore features from the preprocessed data, wherein the one or morefeatures comprise distinguishing and/or informative features forclassification or assessment of the risk of pressure ulcer in thepatient.
 7. The system of claim 6, wherein the one or more featurescomprise a mathematical derivative from the sensor data.
 8. The systemof claim 6, wherein a plurality of the one or more features areconfigured to form patterns that are indicative of a pressure ulcerevent.
 9. The system of claim 6, wherein the system is configured toextract and reduce the one or more features, and the system is furtherconfigured to choose particular features for predicting one or morepressure ulcers.
 10. The system of claim 6, wherein the system isconfigured to extract and reduce the one or more features, and thesystem is further configured to classify and correlate the one or morefeatures with one or more pressure ulcers.
 11. The system of claim 10,wherein the system is configured to classify the one or more featuresusing one or more classification models that are configured forclassifying a future point in time as normal, thereby resulting in noneof the one or more pressure ulcers, or abnormal, thereby resulting inthe one or more pressure ulcers, based on the one or more features. 12.A system comprising a resting device for resting a patient, the restingdevice comprising: a substrate having a contact surface for contactingthe patient, one or more sacs comprising a material and associated withthe contact surface of the substrate, one or more sensors that areincorporated the one or more sacs, and a patient recognition algorithmto detect changes in a user profile; wherein the system is configured toat least (a) combine information and construct the user profile, whereinthe information comprises a first data from a pressure ulcer risk scaleand a second data obtained via the resting device over time, and (b)automatically perform an assessment of a risk of pressure ulcer in thepatient; and wherein the patient recognition algorithm is configured topredict the risk of pressure ulcer in the patient using at least (a)sensor data obtained from the one or more sensors and (b) one or moreobservational information of the patient.
 13. The system of claim 12,wherein the sensor data is combined with the one or more observationalinformation to generate one or more patterns for estimating the risk ofpressure ulcer in the patient.
 14. The system of claim 12, wherein theone or more sensors comprise a pressure sensor, a movement sensor and atemperature sensor, further the system is configured to analyze thesensor data and the one or more observational information to generatethe risk of pressure ulcer in the patient.
 15. The system of claim 14,wherein the one or more observational information comprises one or moredata of the patient, the one or more data comprising: a mobility level,a physical activity level, a mental activity level, a state ofconsciousness, oedema, age, gender, a body-mass index or comorbidities.16. A system comprising a resting device for resting a patient, theresting device comprising: a substrate having a contact surface forcontacting the patient, one or more sacs comprising a material andassociated with the contact surface of the substrate, one or moresensors that are incorporated in the one or more sacs, and a patientrecognition algorithm to detect changes in a user profile; wherein thesystem is configured to at least (a) combine information and constructthe user profile, wherein the information comprises a first data from apressure ulcer risk scale and a second data obtained via the restingdevice over time, and (b) automatically perform an assessment of a riskof pressure ulcer in the patient; and wherein the patient recognitionalgorithm is configured to predict the risk of pressure ulcer in thepatient using at least (a) sensor data obtained from the one or moresensors and (b) a pattern recognition algorithm.
 17. The system of claim16, wherein the system is further configured to at least (a) detectchanges in the user profile of the patient, (b) predict a potentialadverse health effect on the patient and (c) undertake deployment of apressure ulcer prevention strategy.
 18. The system of claim 17, whereinthe system is configured to assign the patient to the pressure ulcerprevention strategy that is commensurate with a level of the risk ofpressure ulcer in the patient.
 19. The system of claim 18, wherein thepressure ulcer risk scale is based on one or more observationalinformation of the patient and gender of the patient.
 20. The system ofclaim 19, wherein the one or more sensors comprise a pressure sensor, amovement sensor and a temperature sensor, further the system isconfigured to analyze the sensor data and the one or more observationalinformation to generate the risk of pressure ulcer in the patient. 21.The system of claim 20, wherein the one or more observationalinformation comprises one or more data of the patient, the one or moredata comprising: a mobility level, a physical activity level, a mentalactivity level, a state of consciousness, oedema, age, gender, body-massindex or comorbidities.